The Department of Computer Sciences offers the master of science and doctor of philosophy degrees in computer sciences. Research specialty areas include artificial intelligence, computational biology, computer architecture, computer graphics, computer networks, computer security, database systems, human–computer interaction, numerical analysis, optimization, performance analysis, programming languages and compilers, systems research, and theoretical computer sciences. The department’s Graduate Advising Committee (GAC) advises all computer sciences graduate students except students who are in dissertator status. See the department website for faculty interests, research activities, courses, facilities, and degree requirements.


Please consult the table below for key information about this degree program’s admissions requirements. The program may have more detailed admissions requirements, which can be found below the table or on the program’s website.

Graduate admissions is a two-step process between academic programs and the Graduate School. Applicants must meet the minimum requirements of the Graduate School as well as the program(s). Once you have researched the graduate program(s) you are interested in, apply online.

Fall Deadline December 15
Spring Deadline The program does not admit in the spring.
Summer Deadline The program does not admit in the summer.
GRE (Graduate Record Examinations) Not required but may be considered if available.
English Proficiency Test Every applicant whose native language is not English, or whose undergraduate instruction was not exclusively in English, must provide an English proficiency test score earned within two years of the anticipated term of enrollment. Refer to the Graduate School: Minimum Requirements for Admission policy: https://policy.wisc.edu/library/UW-1241.
Other Test(s) (e.g., GMAT, MCAT) n/a
Letters of Recommendation Required 3

Applicants with a strong background in computer sciences or a related field are encouraged to apply for admission. At a minimum, the applicant should have some programming experience, including courses in data structures and machine organization, along with a year of college-level mathematics at the calculus level or above. For more information on admissions, visit the department website

A submitted online application is required, consisting of:

  • Resume/CV
  • Statement of purpose
  • Complete supplemental application sections
  • Most up-to-date unofficial transcript(s) from all previous higher education institutions, regardless of whether or not a degree was earned (official transcripts are requested of only recommended applicants); international academic records must be in the original language accompanied by an official English translation. 
  • Test scores and three letters of recommendation as detailed above

Contact admissions@cs.wisc.edu with questions about admissions in the traditional MS or the PhD programs.


Graduate School Resources

Resources to help you afford graduate study might include assistantships, fellowships, traineeships, and financial aid. Further funding information is available from the Graduate School. Be sure to check with your program for individual policies and restrictions related to funding.

Program Resources

Funding is offered to about half of the students to whom admission is offered. Funding is usually in the form of fellowships, teaching assistantships, or research assistantships. Because computer science skills are in demand, students who are admitted without funding are often able to find graduate assistantships on campus.  The department website provides information on funding options and offers suggestions for those who are admitted without department funding.

Minimum Graduate School Requirements

Review the Graduate School minimum academic progress and degree requirements, in addition to the program requirements listed below.

Major Requirements

Mode of Instruction

Face to Face Evening/Weekend Online Hybrid Accelerated
Yes No No No No

Mode of Instruction Definitions

Accelerated: Accelerated programs are offered at a fast pace that condenses the time to completion. Students typically take enough credits aimed at completing the program in a year or two.

Evening/Weekend: ​Courses meet on the UW–Madison campus only in evenings and/or on weekends to accommodate typical business schedules.  Students have the advantages of face-to-face courses with the flexibility to keep work and other life commitments.

Face-to-Face: Courses typically meet during weekdays on the UW-Madison Campus.

Hybrid: These programs combine face-to-face and online learning formats.  Contact the program for more specific information.

Online: These programs are offered 100% online.  Some programs may require an on-campus orientation or residency experience, but the courses will be facilitated in an online format.

Curricular Requirements

Minimum Credit Requirement 51 credits
Minimum Residence Credit Requirement 32 credits
Minimum Graduate Coursework Requirement 26 credits must be graduate-level coursework. Refer to the Graduate School: Minimum Graduate Coursework (50%) Requirement policy: https://policy.wisc.edu/library/UW-1244.
Overall Graduate GPA Requirement 3.00 GPA required.
Refer to the Graduate School: Grade Point Average (GPA) Requirement policy: https://policy.wisc.edu/library/UW-1203.
Other Grade Requirements All required qualifying breadth courses must have a grade of at least AB.
Assessments and Examinations Doctoral students must complete a qualifying process, a preliminary examination, and a dissertation requirement. The qualifying process includes both completion of "qualifying breadth courses" (see Required Courses, below) as well as satisfactory completion of a depth examination in a selected focus area. The preliminary examination is an oral examination demonstrating depth of knowledge in the area of specialization in which research for the dissertation will be conducted. The dissertation requirement consists of conducting a substantial piece of original research in computer science, reporting it in a dissertation that meets the highest standards of scholarship, and explaining and defending the contents of the dissertation in a final oral examination and defense.
Language Requirements No language requirements.
Graudate School Breadth Requirement All doctoral students are required to complete a doctoral minor or graduate/professional certificate. Refer to the Graduate School: Breadth Requirement in Doctoral Training policy: https://policy.wisc.edu/library/UW-1200.

Required Courses

Additional Qualifying Breadth Courses Requirement

PhD students must take one course from each of the bands 1, 2, 3 and 4 listed below. Two of the four courses used to satisfy this requirement must be numbered 700 or above; the remaining two courses must be numbered 500 above. Grades in all courses used for breadth must be at least AB. COMP SCI 839 may satisfy breadth in the band declared by the course instructor at the time of course offering.

One course taken as a graduate student at another institution may satisfy breadth.  A request for this must be made in writing to the faculty member designated to approve equivalence for the respective course on the breadth list. The request should indicate the corresponding UW–Madison course, include a transcript showing a grade equivalent to AB or better, a course syllabus and description.

Band 1
COMP SCI/​E C E  506 Software Engineering3
COMP SCI 536 Introduction to Programming Languages and Compilers3
COMP SCI 537 Introduction to Operating Systems4
COMP SCI 538 Introduction to the Theory and Design of Programming Languages3
COMP SCI 542 Introduction to Software Security3
COMP SCI/​E C E  552 Introduction to Computer Architecture3
COMP SCI 640 Introduction to Computer Networks3
COMP SCI 642 Introduction to Information Security3
COMP SCI 701 Construction of Compilers3
COMP SCI 703 Program Verification and Synthesis3
COMP SCI 704 Principles of Programming Languages3
COMP SCI 706 Analysis of Software Artifacts3
COMP SCI/​E C E  707 Mobile and Wireless Networking3
COMP SCI 736 Advanced Operating Systems3
COMP SCI 739 Distributed Systems3
COMP SCI 740 Advanced Computer Networks3
COMP SCI 744 Big Data Systems3
COMP SCI/​E C E  752 Advanced Computer Architecture I3
COMP SCI/​E C E  755 VLSI Systems Design3
COMP SCI/​E C E  757 Advanced Computer Architecture II3
COMP SCI 758 Advanced Topics in Computer Architecture3
COMP SCI 763 Security and Privacy for Data Science3
COMP SCI/​E C E  782 Advanced Computer Security and Privacy3
Band 2
COMP SCI 534 Computational Photography3
COMP SCI 559 Computer Graphics3
COMP SCI 564 Database Management Systems: Design and Implementation4
COMP SCI 565 Introduction to Data Visualization3
COMP SCI 566 Introduction to Computer Vision3
COMP SCI 570 Introduction to Human-Computer Interaction3
COMP SCI 571 Building User Interfaces3
COMP SCI/​B M I  576 Introduction to Bioinformatics3
COMP SCI 764 Topics in Database Management Systems3
COMP SCI 765 Data Visualization3
COMP SCI/​E C E  766 Computer Vision3
COMP SCI/​ED PSYCH/​PSYCH  770 Human-Computer Interaction3
COMP SCI 774 Data Exploration, Cleaning, and Integration for Data Science3
COMP SCI/​B M I  776 Advanced Bioinformatics3
COMP SCI 784 Foundations of Data Management3
Band 3
COMP SCI/​MATH  513 Numerical Linear Algebra3
COMP SCI/​MATH  514 Numerical Analysis3
COMP SCI 520 Introduction to Theory of Computing3
COMP SCI/​E C E/​I SY E  524 Introduction to Optimization3
COMP SCI/​I SY E/​MATH/​STAT  525 Linear Optimization3
COMP SCI/​I SY E  526 Advanced Linear Programming3
COMP SCI 577 Introduction to Algorithms4
COMP SCI/​I SY E  635 Tools and Environments for Optimization3
COMP SCI 710 Computational Complexity3
COMP SCI/​MATH  714 Methods of Computational Mathematics I3
COMP SCI/​MATH  715 Methods of Computational Mathematics II3
COMP SCI/​I SY E  719 Stochastic Programming3
COMP SCI/​I SY E  723 Dynamic Programming and Associated Topics3
COMP SCI/​I SY E/​MATH/​STAT  726 Nonlinear Optimization I3
COMP SCI/​I SY E  727 Convex Analysis3
COMP SCI/​I SY E/​MATH  728 Integer Optimization3
COMP SCI/​I SY E/​MATH  730 Nonlinear Optimization II3
COMP SCI 787 Advanced Algorithms3
COMP SCI 880 Topics in Theoretical Computer Science3
Band 4
COMP SCI/​E C E/​M E  532 Matrix Methods in Machine Learning3
COMP SCI/​E C E/​M E  539 Introduction to Artificial Neural Networks3
COMP SCI 540 Introduction to Artificial Intelligence3
COMP SCI/​E C E  561 Probability and Information Theory in Machine Learning3
COMP SCI/​E C E  760 Machine Learning3
COMP SCI/​E C E  761 Mathematical Foundations of Machine Learning3
COMP SCI 762 Advanced Deep Learning3
COMP SCI 769 Advanced Natural Language Processing3
COMP SCI/​B M I  771 Learning Based Methods for Computer Vision3
COMP SCI/​E C E/​STAT  861 Theoretical Foundations of Machine Learning3

Graduate School Policies

The Graduate School’s Academic Policies and Procedures provide essential information regarding general university policies. Program authority to set degree policies beyond the minimum required by the Graduate School lies with the degree program faculty. Policies set by the academic degree program can be found below.

Major-Specific Policies

Prior Coursework

Graduate Credits Earned at Other Institutions

Subject to faculty approval, one graduate course taken elsewhere may be used for breadth. Other than that, no credits of graduate coursework from other institutions are allowed to satisfy requirements.

Undergraduate Credits Earned at Other Institutions or UW-Madison

No credits from a UW–Madison undergraduate degree are allowed to satisfy requirements.

Credits Earned as a Professional Student at UW-Madison (Law, Medicine, Pharmacy, and Veterinary careers)

Refer to the Graduate School: Transfer Credits for Prior Coursework policy.

Credits Earned as a University Special student at UW–Madison

Refer to the Graduate School: Transfer Credits for Prior Coursework policy.


At the end of any regular (non-summer) semester, a student is considered to be making satisfactory academic progress (SAP) if the following conditions are all satisfied:

  • Before achieving dissertator status: the student has completed at least 6 (if full load) or 3 (if part load) credits of approved courses during the semester.
  • After achieving dissertator status: the student has satisfactorily completed at least three credits of courses approved by the student’s major professor.
  • The student has removed all Incomplete grades from any previous regular semester or summer session.
  • The student has passed any required exams and procedures within designated time limits.

Any graduate student who fails to make satisfactory academic progress (SAP) during two consecutive regular semesters (fall and spring, or spring and fall) will be dismissed from the department at the end of the subsequent summer session. Any graduate student who fails to make satisfactory academic progress (SAP) due to missed deadlines will be dismissed from the department at the end of the subsequent summer session.

Advisor / Committee

A member of the graduate advising committee must formally approve all graduate schedules each semester until a student is in dissertator status.

Credits Per Term Allowed

15 credits

Time Limits

Students must pass the qualifying process by the end of the sixth semester.

The preliminary exam must be taken within two regular (non-summer) semesters after the deadline for the qualifying exam.

Refer to the Graduate School: Time Limits policy.

Grievances and Appeals

These resources may be helpful in addressing your concerns:

Students should contact the department chair or program director with questions about grievances. They may also contact the L&S Academic Divisional Associate Deans, the L&S Associate Dean for Teaching and Learning Administration, or the L&S Director of Human Resources.



Professional Development

Graduate School Resources

Take advantage of the Graduate School's professional development resources to build skills, thrive academically, and launch your career. 

Program Resources

The Department of Computer Sciences hosts many professional development opportunities, including job fairs, workshops, seminars, talks, employer information sessions, mentoring, and student socials. The Department of Computer Sciences' student organizations, Student-ACM (SACM) and Women's ACM (WACM), are active partners in providing professional development opportunities for computer sciences graduate students.

Learning Outcomes

  1. Articulates research problems, potentials, and limits with respect to theory, knowledge, or practice within the field of study.
  2. Formulates ideas, concepts, designs, and/or techniques beyond the current boundaries of knowledge within the field of study.
  3. Creates research, scholarship, or performance that makes a substantive contribution.
  4. Demonstrates breadth within their learning experiences.
  5. Advances contributions of the field of study to society.
  6. Communicates complex ideas in a clear and understandable manner.
  7. Fosters ethical and professional conduct.


Visit the CS website to view our department faculty and staff.